Aim: DNA methylation is a key epigenetic mechanism regulating gene expression. Identifying differentially methylated regions is integral to DNA methylation analysis and there is a need for robust tools reliably detecting regions with significant differences in their methylation status. Materials & methods: We present here a reproducibility-optimized test statistic (ROTS) for detection of differential DNA methylation from high-throughput sequencing or array-based data. Results: Using both simulated and real data, we demonstrate the ability of ROTS to identify differential methylation between sample groups. Conclusion: Compared with state-of-the-art methods, ROTS shows competitive sensitivity and specificity in detecting consistently differentially methylated regions.
CITATION STYLE
Suni, V., Seyednasrollah, F., Ghimire, B., Junttila, S., Laiho, A., & Elo, L. L. (2020). Reproducibility-optimized detection of differential DNA methylation. Epigenomics, 12(9), 747–755. https://doi.org/10.2217/epi-2019-0289
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